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Target classification with data from multiple sensors

Target classification with data from multiple sensors

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14th conference on signal and data processing of small targets

作者： Drummond, OE CyberRnD Inc Culver City CA 90230 USA

ISBN: (纸本)0819444782

the methods used in the classification of multiple small targets can be very different from the methods commonly used in traditional pattern recognition. First, there may be characteristics of the features for. each target class that can permit simpler computations than other features. In addition, in classifying targets, the target tracks are updated as new data becomes available and hence there can be a sequence of feature measurements that are available for the target classification process. In addition, with multiple targets, the a priori information may be in a form that make the classification processing for one target dependent on the classification processing of other targets. these aspects of target classification that make that processing different from traditional pattern recognition are the concern of this paper. To limit the length of the paper, the scope is restricted to classification tasks that allow the linear-Gaussian assumption to be used. Also, the data used in the classification process is restricted to features, i.e., no attributes, and the assumption is the tracker does not employ feature-aided tracking. While these assumptions simplify the discussion, the methods used could be modified to permit classification of a broad scope of classification tasks.

关键词： multiple target tracking features target typing detection classification recognition identification and discrimination automatic target recognition (ATR) multiple models Bayesian methods and Kalman filter

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High-resolution radar ranging for multiple targets

High-resolution radar ranging for multiple targets

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14th conference on signal and data processing of small targets

作者： Wang, Z Willett, P Bar-Shalom, Y Blair, WD Univ Connecticut Storrs CT 06269 USA

ISBN: (纸本)0819444782

the similarity between the multiple-target radar ranging problem and the multi-user detection problem in CDMA is drawn: in CDMA, users' bits modulate distinct but correlated signature signals;while, in radar, the "bits" are range-bin occupancies and the "signatures" correspond to the known transmitted signal translated to be centered on the appropriate range bin. the analogy is useful: there has been a great deal of recent experience in CDMA, and one of the best and fastest algorithms uses a variant of probabilistic data association (PDA, the target-tracking philosopk). PDA can be augmented by group decision feedback (GDF) - another idea from CDMA - to refine the target delay- estimates;and finally minimum description length (MDL) is applied to estimate the munber of targets. Simulation examples are given to illustrate the resolution of closely-spaced targets within what would normally- be thought the same range bin. Its performance is also compared with the Cramer-Rao lower bound (CRLB) and the alternating projection (AP) algorithm.

关键词： Personal digital assistants Radar Detection and tracking algorithms Target detection Expectation maximization algorithms signal detection signal to noise ratio Ranging Correlation function Modulation

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the Network Centric Warfare Paradigm: the primacy of estimation, tracking and data fusion algorithms for implementation of this vision

The Network Centric Warfare Paradigm: The primacy of estimat...

引用

14th conference on signal and data processing of small targets

作者： Gray, JE Smith-Carroll, AS McCabe, DH Murray, WJ Alouani, AT USN Ctr Surface Warfare Dahlgren Div Syst Res & Technol Dept Dahlgren VA 22448 USA

ISBN: (纸本)0819444782

What underpins this vision as axiomatic is the mantra "Information is power". Besides the necessary requirement of information exchange networks with sufficient bandwidth and computational power to treat the data being passed around the network;, algorithms are required to make sense of the data. It is estimation algorithms that turn the straw (data) into gold (information). Both proper execution and improvements in estimation algorithms are the enabling technology that facilitates the formation and usage of data across the envisioned warfare networks. We focus on some of the requirements that are driving the formation of these networks from a surface navy perspective in terms of estimation. We also discuss how these requirements focus the design of potentially new algorithms. We also discuss some of the crucial issues that may drive future requirements and algorithms.

关键词： Military operations

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Hybrid tracking algorithm using MHT and PMHT

Hybrid tracking algorithm using MHT and PMHT

引用

14th conference on signal and data processing of small targets

作者： Dunham, DT Hutchins, RG Independent Contractor (United States) Naval Postgraduate School (United States)

ISBN: (纸本)0819444782

Since the early 1990s, significant research has been done on a relatively new algorithm called the Probabilistic MultiHypothesis Tracker (PMHT). the majority of this research has concluded that there are a few weaknesses with this approach to tracking targets in the presence of clutter. First, the number of targets that are being tracked needs to be known a priori. Second, in order for the algorithm to operate properly, a very good initiation must be performed. Without a very close initiation, the PMHT usually fails to "lock on" to the target correctly. To address both of these issues, a hybrid approach is proposed. this hybrid approach will use a Multi-Hypothesis Tracking (MHT) algorithm to initiate new tracks and to continue tracking them until a track is stable. then it will hand these tracks off to the PMHT to maintain. the MHT is very good at initiating new tracks, and the PMHT is best at maintaining multiple tracks because the algorithm's complexity with tracking additional targets grows linearly as opposed to exponentially'.

关键词： multiple targets hybrid PMHT MHT initialization

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Mysterious computational complexity of particle filters

Mysterious computational complexity of particle filters

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14th conference on signal and data processing of small targets

作者： Daum, F Huang, J Raytheon Elect Syst Sudbury MA 01776 USA

ISBN: (纸本)0819444782

Particle filtering (PF) is a relatively new method to solve the nonlinear filtering problem, which is very general and easy to code. the main issue with PF is the large computational complexity. In particular, for typical low dimensional tracking problems, the PF requires 2 to 4 orders of magnitude more computer throughput than the EKF, to achieve the same accuracy. It has been asserted that the PF avoids the curse of dimensionality, but there is no formula or theorem that bounds or approximates the computational complexity of the PF as a function of dimension (d). In this paper, we will derive a simple back-of-the-envelope formula that explains why a carefully designed PF should mitigate the curse of dimensionality for typical tracking problems, but that it does not avoid the curse of dimensionality in general. this new theory is related to the fact that the volume of the d dimensional unit sphere is an amazingly small fraction of the d dimensional unit cube, for large d.

关键词： Error analysis Monte Carlo methods Nonlinear filtering Particles Particle filters Filtering (signal processing) Optical spheres Electronic filtering Probability theory Statistical analysis

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Probability-of-detect-based beam pointing for multitarget tracking with electronically scanned radars

Probability-of-detect-based beam pointing for multitarget tr...

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14th conference on signal and data processing of small targets

作者： Register, A Brown, G Blair, WD Georgia Tech Research Institute (United States)

ISBN: (纸本)0819444782

Since the time and energy of phased array radars are under great demand in modem combat systems, methods that conserve those resources are very important. Two opportunities for conserving radar resources that have not been fully exploited when tracking closely-spaced objects with currently deployed systems are revisit time selection (i.e., time to make a measurement) and beam boresight placement. While these two functions are somewhat coupled, this paper addresses only the problem of beam pointing. Previously, a methodology for track management for phased array radars hinged on the concept of organizing tracks into, so called, dwell groups that included closely-spaced targets that could be illuminated with a single beam. Pointing angle for a dwell group was determined using a geometry-based approach. While the geometry-based approach was useful in improving the entire track management function, it was known to be sub-optimal in that the detection characteristics of the targets were not considered. this paper addresses an improved methodology for assigning membership in dwell groups and selecting dwell pointing angles.

关键词： multitarget tracking phased array radar signal processing beam pointing

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Unresolved target detection - Detailed case study of a particular technique assuming correct calibration

Unresolved target detection - Detailed case study of a parti...

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14th conference on signal and data processing of small targets

作者： McCabe, DH Smith-Carroll, AS Gray, JE USN Ctr Surface Warfare Dahlgren Div Syst Res & Technol Dept Dahlgren VA 22448 USA

ISBN: (纸本)0819444782

A particular method of detecting unresolved targets using simulated monopulse radar data is examined in detail. the system is assumed to be correctly calibrated i.e. the decision boundary is calculated based on the true values governing the hypothesis that only a single target is present in the range cell. the system performance is analyzed under varying values for target ranges, angles between the beam pointing direction and the actual off-boresight angle of the targets, waveform power and number of pulses. It is shown that these parameters have a pronounced impact on the Boundary, Metric and Decision Surfaces. the False Alarm probability for a single target as a function of waveform power is considered, as also are the detection probabilities when two targets are present. the important issue of locating the decision point on the Boundary Surface is briefly discussed.

关键词： unresolved targets radar cross-section Neyman Pearson hypothesis testing detection probability

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Maximum likelihood angle extractor in the presence of sea-surface multipath

Maximum likelihood angle extractor in the presence of sea-su...

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14th conference on signal and data processing of small targets

作者： Sinha, A Blair, WD Kirubarajan, T Bar-Shalom, Y Univ Connecticut Dept Elect & Comp Engn Storrs CT 06268 USA

ISBN: (纸本)0819444782

In the presence of sea-surface multipath monopulse radar signals from a low elevation target have three alternative paths in addition to the direct (radar-to-target) path due to reflections from the sea surface. the specular reflection causes significant signal fading. the diffuse reflection causes an approximately constant bias to the in-phase component of the monopulse ratio, which is the standard extractor of the direction of arrival (DOA) in the monopulse processing. the diffuse reflection also causes higher standard deviation to the in-phase component of the monopulse ratio. In this paper we propose a maximum likelihood (ML) angle extraction technique for low elevation targets of known average signal strength having a Rayleigh fluctuation. the results show that this method reduces the error of the estimated angle compared to the conventional monopulse ratio estimator. Subsequently, the ML angle extractor is modified for the unknown average signal strength case. this modified angle extractor has only a small performance degradation compared with the known average signal strength case, but it performs much better than the monopulse ratio based estimator. this angle extractor reduces the root mean square error (RMSE) by more than 50% in the signal processing stage when used in a low flying target (sea skimmer) tracking scenario.

关键词： Radar Reflection signal to noise ratio Specular reflections Error analysis signal processing Detection and tracking algorithms Silicon Analytical research Computer engineering

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Expected likelihood for tracking in clutter with particle filters

Expected likelihood for tracking in clutter with particle fi...

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14th conference on signal and data processing of small targets

作者： Marrs, A Maskell, S Bar-Shalom, Y QinetiQ Ltd Malvern Technol Ctr Malvern Worcs England

ISBN: (纸本)0819444782

the standard approach to tracking a single target in clutter, using the Kalman filter or extended Kalman filter, is to gate the measurements using the predicted measurement covariance and then to update the predicted state using probabilistic data association. When tracking with a particle filter, an analog to the predicted measurement covariance is not directly available and could only be constructed as an approximation to the current particle cloud. A common alternative is to use a form of soft gating, based upon a Student's-t likelihood, that is motivated by the concept of score functions in classical statistical hypothesis testing. In this paper, we combine the score function and probabilistic data association approaches to develop a new method for tracking in clutter using a particle filter. this is done by deriving an expected likelihood from known measurement and clutter statistics. the performance of this new approach is assessed on a series of bearings-only tracking scenarios with uncertain sensor location and non-Gaussian clutter.

关键词： tracking probabilistic data association particle filters

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Adaptive sensor management in target tracking

Adaptive sensor management in target tracking

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14th conference on signal and data processing of small targets

作者： Sworder, DD Boyd, JE Univ Calif San Diego Dept Elect & Comp Engn La Jolla CA 92093 USA

ISBN: (纸本)0819444782

Model-based. path estimation algorithms are commonly derived from a linear kinematic equation and an expansive observation model. the premise that the measurement region is all-inclusive simplifies the performance analysis, but it does not describe the relevant characteristics of some sensors. Most sensors have an active region. If the region contains, the target. a noisy location measurement is made. Alternatively, no location measurement is returned. there is a clear tradeoff between measurement acuity and broad coverage. A sensor that adapts its active region to the most likely target location should achieve higher quality tracking and identification. However. effective utilization of this flexibility requires an accurate determination of the conditional distribution of the target-state. In this paper, the Gaussian Wavelet Estimator is used in an adaptive algorithm for sensor management. It is shown that the adaptive window provides performance that is superior to that achieved using a fixed window of comparable cover probability.

关键词： nonlinear filters target tracking data fusion

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